Idiopathic normal pressure hydrocephalus: a systematic review and a streamlined six-step algorithm endorsed by the Italian Society of Neurosurgery (SINCH)

Abstract

Introduction: Idiopathic normal pressure hydrocephalus (iNPH) is a treatable neurodegenerative disorder characterized by a triad of gait disturbance, cognitive impairment, and urinary incontinence. Early diagnosis and timely intervention are crucial for optimal outcomes. However, the diagnosis of iNPH remains challenging due to its variable presentation and overlap with other neurological conditions.

Evidence acquisition: A comprehensive review of the literature was conducted to identify current diagnostic criteria and treatment strategies for iNPH. Based on this review, a novel, six-step algorithm was developed to streamline the diagnostic process and improve patient outcomes.

Evidence synthesis: The proposed algorithm includes the following six steps: 1) suspect diagnosis of iNPH: Identification of core clinical features (gait disturbance, cognitive impairment, and urinary incontinence) and radiological evidence of ventricular enlargement; 2) investigate probable iNPH: detailed neuropsychological assessment, gait analysis, and urodynamic studies to confirm the diagnosis; 3) high-volume lumbar puncture: evaluation of the clinical response to CSF drainage, including improvements in gait, cognition, and urinary function; 4) evaluation after HVLP: assessment of the duration and magnitude of symptom improvement after lumbar puncture; 5) shunt surgery: indication for shunt surgery in patients with a positive response to CSF drainage; 6) infusion test and intracranial pressure measurement: alternative diagnostic tools for cases where the diagnosis remains uncertain.

Conclusions: The proposed algorithm provides a structured approach to the diagnosis and management of iNPH. By combining clinical, radiological, and neurophysiological assessments, clinicians can improve diagnostic accuracy and optimize patient outcomes. Further research is needed to validate this algorithm in larger patient populations and to develop more sensitive and specific biomarkers for iNPH.